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I believe this is conflating distribution with randomness. Having played too many games and rolled too many real and pseudorandom dice, i know streaks are the

by elif 5y ago

I believe this is conflating distribution with randomness. Having played too many games and rolled too many real and pseudorandom dice, i know streaks are the rule not the exception, and that completely missed rolls likewise expectable. Using this model of randomness, i tried to create sequences that matched. The result is it says i have 60 year old brain. I did the prompt again, but simply /ensured there were no missed rolls/ and i have an under 60 brain? In reality, i believe the odds of rolling all 6 sides using 10 dice rolls are relatively low... but in order to be "random" enough that seems like a prerequisite??

want2takearide 5y ago
I had the same issue. I generated random numbers and still got over 60 years old. I had to dive deep into it, and it turns out that the original paper is shit. They ask participants to make sequences that are as random as possible but they use Kolmogorov complexity as a measure, which (surprise) doesn't actually measure randomness but complexity. Random distributions tend to have lower complexity than what humans generate; see [1] Fig. 4. Here are the complexity scores for different sequences if you want to lose more sleep over this: [2]. At least the authors were nice enough to be open about their data, so props I guess. [1]: https://link.springer.com/content/pdf/10.3758/s13428-015-0574-3.pdf https://link.springer.com/content/pdf/10.3758/s13428-015-057... [2]: https://github.com/algorithmicnaturelab/HumanBehavioralComplexity/blob/master/lifespan.csv https://github.com/algorithmicnaturelab/HumanBehavioralCompl...
- m3047 5y ago
  Maybe the null hypothesis needs to be that older people have more experience of "random" and therefore expect or tolerate more variance before rejecting "chance". But they say that the effect is relatively small, or that their age guessing is "not as good as we had expected". I'd be prone to misinterpreting the question. If somebody asked me if the sequence "HTHTHTHT" is more or less likely to occur than “HTHHTHTT” I'd be confused. Ok, are they rejecting that they're equally likely out of hand, and if so why? At least subconsciously. If forced to suggest one or the other I'd offer the latter even though I know it's not mathematically correct. Additionally most of the problems I deal with have to do with probability within a continuous run and in a run of 1000 heads/tails and some quick and dirty Monte Carlo I get: m3047@sophia:~/temp> ./sequences.py | grep -E 'HTHTHTHT|HTHHTHTT' 11 HTHTHTHT 6 HTHHTHTT m3047@sophia:~/temp> ./sequences.py | grep -E 'HTHTHTHT|HTHHTHTT' 8 HTHTHTHT 3 HTHHTHTT m3047@sophia:~/temp> ./sequences.py | grep -E 'HTHTHTHT|HTHHTHTT' 5 HTHTHTHT 4 HTHHTHTT So I'd be wrong in practice at least with whatever PRNG is being utilized or maybe I'm just lucky. Always good to test and ask questions.
zarriak 5y ago
It would be nice if they had a different page where you could see in real time or after you submit a sample of 10 how random their model thought the inputs you were giving were.

by elif 5y ago

want2takearide 5y ago

I had the same issue. I generated random numbers and still got over 60 years old. I had to dive deep into it, and it turns out that the original paper is shit. They ask participants to make sequences that are as random as possible but they use Kolmogorov complexity as a measure, which (surprise) doesn't actually measure randomness but complexity. Random distributions tend to have lower complexity than what humans generate; see [1] Fig. 4. Here are the complexity scores for different sequences if you want to lose more sleep over this: [2]. At least the authors were nice enough to be open about their data, so props I guess. [1]: https://link.springer.com/content/pdf/10.3758/s13428-015-0574-3.pdf https://link.springer.com/content/pdf/10.3758/s13428-015-057... [2]: https://github.com/algorithmicnaturelab/HumanBehavioralComplexity/blob/master/lifespan.csv https://github.com/algorithmicnaturelab/HumanBehavioralCompl...

m3047 5y ago
Maybe the null hypothesis needs to be that older people have more experience of "random" and therefore expect or tolerate more variance before rejecting "chance". But they say that the effect is relatively small, or that their age guessing is "not as good as we had expected". I'd be prone to misinterpreting the question. If somebody asked me if the sequence "HTHTHTHT" is more or less likely to occur than “HTHHTHTT” I'd be confused. Ok, are they rejecting that they're equally likely out of hand, and if so why? At least subconsciously. If forced to suggest one or the other I'd offer the latter even though I know it's not mathematically correct. Additionally most of the problems I deal with have to do with probability within a continuous run and in a run of 1000 heads/tails and some quick and dirty Monte Carlo I get: m3047@sophia:~/temp> ./sequences.py | grep -E 'HTHTHTHT|HTHHTHTT' 11 HTHTHTHT 6 HTHHTHTT m3047@sophia:~/temp> ./sequences.py | grep -E 'HTHTHTHT|HTHHTHTT' 8 HTHTHTHT 3 HTHHTHTT m3047@sophia:~/temp> ./sequences.py | grep -E 'HTHTHTHT|HTHHTHTT' 5 HTHTHTHT 4 HTHHTHTT So I'd be wrong in practice at least with whatever PRNG is being utilized or maybe I'm just lucky. Always good to test and ask questions.

zarriak 5y ago

It would be nice if they had a different page where you could see in real time or after you submit a sample of 10 how random their model thought the inputs you were giving were.